Does mobile data devour a quarter of South Africans’ income?

Agitating that #DataMustFall, some have claimed that South Africans spend close to a quarter of their income on data. But surveys from South Africa’s national statistics agency and the University of Cape Town tell a different story.

South Africans have taken to Twitterandparliament to rally against the high cost of mobile data. Using the hashtag #DataMustFall, people are calling on government and regulators to rein in network providers’ data charges.

In a panel discussion on the topic Sipho Ngwenya, an information technology engineer, told ANN7 viewers that South Africans currently spend “24.7% of income for data and that is quite a lot”.

Does data really devour a quarter of South Africans’ income? We took a look.

First the head of the household was questioned about whether they had access to a fixed telephone and internet, among other questions.

Then another household member older than 15 was randomly selected to tell the researchers about their access to television, radio, public phones, mobile phones and computers. This household member was also asked to state how much income they received from sources such as a salary, self employment, pension or scholarship.

Based on a question about how much this person spent on cellphone use in the last month, Research ICT Africa calculated that airtime and subscriptions gobbled up 24.7% of South Africans income.

‘The rich don’t really have an affordability problem’

A woman sits beside the road in Qunu in the Eastern Cape in July 2013. A study found that in one rural municipality in the province residents spent R85 of an average income of R388 on cellphone use. Photo: AFP/CARL DE SOUZA

Already the claim that South African spend almost a quarter of their income on data is incorrect. That is because the survey questioned people about how much they spent on cellphone use in total.

Lecturer and visiting research associate at the University of the Witwatersrand, Indra de Lanerolle, leads a programme on internet use in Africa. He told Africa Check that when talking about data affordability the question first needs to be asked “affordable for whom?”

“To take an average across all income groups is probably not very illuminating,” De Lanerolle added. “The rich don’t really have an affordability problem. The poor do.”

Telecommunications regulation specialist and economist at Acacia Economics, Ryan Hawthorne, also said that the 24.7% figure Research ICT Africa calculated seems unlikely, even it if relates to cellphone spend in total.

Stats SA: 2.8% spent on communication in 2010/11

A student uses her mobile phone in October 2010 at the University of the Witwatersrand in Johannesburg. The current #DataMustFall campaign wants it to be more affordable for students to access educational material online. Photo: AFP/STEPHANE DE SAKUTIN

The average South African household spent an estimated R95,183 during 2010/11, according to the survey. An average of R2,702 went to communication in that year.

“Households spent most of their income on housing, water, electricity, gas and other fuels (at 32.0%), followed by transport (at 17.1%),” Koka told Africa Check. Then came miscellaneous goods and services such as car payments and medical insurance and food (at 12.8%).

Previous income and expenditure surveys showed that household spend on communication has stayed below 5%.

Africa Check asked Research ICT Africa to comment on the differences between their study results and the income and expenditure survey. By the time of publication they have not replied yet. (Note: We will update this report if they do.)

NIDS: 3% spent on cellphones in 2014/15

The latest NIDS data was collected in 2014/2015from 37,396 individuals in 11,895 households. Hawthorne told Africa Check that the average household spent R6,899 per month, with 3% of that (R206) going to cellphone and airtime bills (which could include data).

Breaking down the data by income groups, the bottom 20% of income earners spent 4.8% of total household expenditure on cellphone use while those in the top 20% spent 2.3%.

Income group

Average household spend per month

Average household cellphone spend per month

Cellphone spend as % of household spend

1

R1,090

R52

4.8%

2

R1,984

R88

4.4%

3

R3,184

R136

4.3%

4

R5,920

R191

3.2%

5

R22,330

R503

2.3%

Conclusion: The claim is incorrect

People have claimed that South Africans spend close to a quarter of their income on data, based on research conducted by Research ICT Africa.

But the study took into account money spent on both data and airtime. It is also at odds with two much larger nationally representative studies.

Stats SA’s most recent Income and Expenditure Survey (for 2010/11) showed that expenditure on communication, including data and airtime, only accounted for 2.8% of households’ total expenditure.

Data from another nationally representative study, the National Income Dynamics Study, showed that households spent 3% of their income on cellphone use in 2014/15.

Comment on this report

Hi AfricaCheck. First of all – Love what you’re doing, with a capital L. What makes this work that you’re doing so good is that you’re using scientific data, openly available to make openly reproducible claims about facts in the world we live in. That’s rad, and important in a time of demagogues twisting everything.

However, I’m writing from a researcher’s point of view. I see you’ve used the DataFirst datasets, which I’m familiar with. They are part of a huge network of survey data repositories – http://www.ihsn.org/home/ as I’m sure you’re aware. While most of these repositories adopt stringent quality criteria and a common metadata format (DDI) for their data – making it highly reputable, re-usable and machine-readable, many do not use persistent identifiers in their datasets.

Persistent unique identifiers are ways to uniquely identify datasets (duh), and the most common system for doing this is the handle (handle.net) or Digital Object Identifier (DOI) system. These are widely used for documents, but we have been pushing for a while in the Open Science movement to use them for datasets and software too. The THOR project – https://project-thor.eu/ is leading the way in developing human and technical infrastructure to do this.

Another aspect of the Open Science movement is ensuring attribution for lots of different kinds of work, so ensuring that the people who collected, curated, cleaned, published this data get recognition for it. The Open Researcher and Contributor ID (ORCID – http://orcid.org) system is a means for uniquely identifying _people_. When objects are linked to people in unambiguous ways, it becomes possible to build metrics for how much impact those things and people have.

This brings me back to the original, seemingly nerdy and pedantic but very important point – it would have been great if you could have used a digital object identifier in the article instead of the link to the repository. This is because the DOI metadata tracks who is “citing” it, ie who links back to it. Your readership is massive, so effectively, you would be giving a huge boost to the researcher(s) and data repository which you cite. I know this may seem like a trivial difference, but it actually has huge implications for the visibility and evaluation of researchers who undertake the thankless work which allows you to do such a good job of checking facts with reliable data.

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For democracy to function, public figures need to be held to account for what they say. The claims they make need to be checked, openly and impartially. Africa Check is an independent, non-partisan organisation which assesses claims made in the public arena using journalistic skills and evidence drawn from the latest online tools, readers, public sources and experts, sorting fact from fiction and publishing the results.